Journal of Digital Information Management Dianjin Yang 22 4 2024 https://10.6025/jdim/2024/22/4/117-123 https://www.dline.info/fpaper/jdim/v22i4/jdimv22i4_1.pdf With the rapid development of the internet and digital music, competition among music platforms has become intense. This study focuses on NetEase Cloud Music and proposes a development strategy based on the decision tree algorithm. By collecting user behavior data and constructing decision tree models, the study predicts user preferences and needs, providing personalized recommendations and services on the music platform. Experimental results of this strategy show that it effectively improves user satisfaction and platform profitability. Compared to traditional recommendation algorithms, the decision tree algorithm exhibits better interpretability and accuracy, enabling a deeper understanding of user preferences and behavior patterns, thus providing more precise content recommendations. This innovative development strategy for music platforms helps better meet user demands, achieve sustained growth, and gain competitive advantages.